Wavelet based medical image compression through prediction

Muhammad Younus, Muhammad Habib Khan, Yao-Tien Chen
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引用次数: 9

Abstract

This paper offers a simple and lossless compression method for compression of medical images. Method is based on wavelet decomposition of the medical images followed by the correlation analysis of coefficients. The correlation analyses are the basis of prediction equation for each sub band. Predictor variable selection is performed through coefficient graphic method to avoid multicollinearity problem and to achieve high prediction accuracy and compression rate. The method is applied on MRI and CT images. Results show that the proposed approach gives a high compression rate for MRI and CT images comparing with state of the art methods.
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基于小波预测的医学图像压缩
本文提出了一种简单、无损的医学图像压缩方法。该方法首先对医学图像进行小波分解,然后进行相关系数分析。相关分析是各子带预测方程的基础。通过系数图法选择预测变量,避免了多重共线性问题,实现了较高的预测精度和压缩率。将该方法应用于MRI和CT图像。结果表明,与现有方法相比,该方法对MRI和CT图像具有较高的压缩率。
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